This research explores how Large Language Models are addressing critical challenges in software security by offering more efficient vulnerability detection than traditional methods.

• LLMs analyze code structures and identify security patterns with higher accuracy
• Models like GPT, BERT and CodeBERT overcome limitations of static/dynamic analysis techniques
• AI-powered approaches reduce false positives while handling increasingly complex software systems
• LLMs can generate repair suggestions, moving beyond mere detection

For security professionals, this represents a paradigm shift in how vulnerabilities are identified and addressed, potentially reducing security incidents while improving development efficiency.

LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights